New York NOAA Dashboard

data("ny_noaa") 

ny_noaa = 
  ny_noaa |>
 na.omit(ny_noaa)

Column

Chart A

ny_noaa_summary <- ny_noaa %>%
  summarise(min_prcp = min(prcp, na.rm = TRUE), 
            max_prcp = max(prcp, na.rm = TRUE))

box_plot <- plot_ly(ny_noaa, 
                    y = ~prcp, 
                    type = "box", 
                    name = "Precipitation") %>%
  layout(title = "Box Plot of Minimum and Maximum Precipitation",
         yaxis = list(title = "Precipitation (inches)"))

box_plot

Column

Chart B

ny_noaa_filtered <- ny_noaa %>%
  select(date, prcp, snow) %>%
  filter(!is.na(prcp) & !is.na(snow))

plot <- plot_ly(ny_noaa_filtered, x = ~date) %>%
  add_lines(y = ~prcp, name = 'Precipitation', line = list(color = 'blue')) %>%
  add_lines(y = ~snow, name = 'Snow', line = list(color = 'white')) %>%
  layout(title = 'Precipitation and Snow Over Time',
         xaxis = list(title = 'Date'),
         yaxis = list(title = 'Amount'),
         legend = list(x = 0, y = 1))
         
plot

Chart C

avg_prcp_by_date <- ny_noaa %>%
  group_by(date) %>%
  summarize(avg_prcp = mean(prcp, na.rm = TRUE))

plot_2 <- plot_ly(avg_prcp_by_date, x = ~date, y = ~avg_prcp, type = 'bar') %>%
  layout(title = "Average Precipitation by Date",
         xaxis = list(title = "Date"),
         yaxis = list(title = "Average Precipitation"))


plot_2